Financial frauds are increasing day by day over the world the financial frauds has been increased by 56% since last 10 years. To reduce the frauds and to avoid corruption we have built this application.
What it does
It predicts whether the person is eligible for loan or not based on financial history. We have used ML algorithms like
- Artificial Neural Networks
- K Nearest Neighbors
- Decision Trees
- Random Forest
- Random Forest + AdaBoost
With best results from Random Forest and Adaboost we have predicted. Tells whether loan will be approved or not.
How we built it
We built using Flask framework, python libraries and machine learning algorithms.
Challenges we ran into
Deploying the framework, running different ml algorithms.
Accomplishments that we're proud of
Successfully completed the prediction part with 65% accuracy
What we learned
Teamwork, brushing up concepts.
What's next for Credit Baba
Next we will deploy it and add db to it